AI Shifts to Value Driver from Baseline Diligence Requirement in 2026

In 2025, AI proved its value across the deal lifecycle. In 2026, the expectation changes. AI is no longer a differentiator; it’s now table stakes. Buyers see it as core deal infrastructure, not an optional tool. This shift is reshaping how deal teams work, how founders prepare, and how investors judge risk and value. It also resets who gets acquired, and who might get left behind.

AI as the New Baseline

For years, deal teams tested AI in controlled, narrow settings. They used it to summarize, tag, and automate simple workflows.

Today, dealmakers expect AI to sit inside daily execution. Investors assume it shapes valuation and risk. Regulators insist on clear controls and guardrails. And teams that lag behind feel it in lost speed, higher friction, and weaker confidence in outcomes.

This shift did not happen because the technology suddenly became more capable. It happened because behavior changed. AI became normal. It became part of the dealmaking rhythm. The industry crossed a line, from experimentation to dependence.

Defensible AI vs. Surface-Level Features

This behavioral shift is forcing buyers to redraw the line between real AI and the illusion of it. The market is expected to see 200 to 300 initial public offerings in 2026, many of which will be powered by AI. Not all may stand up to diligence. Buyers are now asking even sharper questions, on proprietary data, models training the data, whether the model is essential to the product, if a company can prove performance, accuracy, and reliability, and if the AI is repeatable at scale.

The answers determine whether a target earns a premium or a pass. Defensible AI rests on owned data, proven models, and the talent required to maintain them. Surface-level AI relies on generic APIs or bolt-on features that anyone else can replicate.

Founders who fail to prepare for this distinction risk losing deals before they start. Investors already know this. They are steering portfolio companies to build durable data assets, document model performance, and strengthen governance. Without these steps, a company will struggle to clear the diligence bar now expected in 2026.

How Diligence Is Changing

Diligence is where the new AI baseline becomes most visible. AI now prepares files, organizes data, flags anomalies, and speeds compliance reviews. That part is familiar. What’s new is the level of scrutiny around the target’s own AI claims. Deal teams now map the entire AI stack including:

• Data sources and data rights
• Model lineage and model accuracy
• Infrastructure scalability
• Security architecture
• AI governance and auditability
• Regulatory exposure

Teams also test how a target’s AI integrates with their own systems. They assess risk earlier. They quantify value creation faster. They uncover red flags in days that once took weeks.

This deeper review has practical effects. It changes who is involved in diligence. It changes the questions asked. It changes the speed and the tone of deal discussions. And it raises expectations for what founders must disclose, long before a deal is signed.

A New Approach to Integration Planning

Once the deal closes, AI continues to shape the next phase. Integration used to be reactive. Teams struggled to track synergies, manage talent, and monitor long-term performance.

Now AI helps teams track synergy delivery in real time; test future scenarios quickly; monitor integration risks early; align teams around a single source of truth and keep decisions tied to the investment thesis.

Agentic AI goes even further. It learns from past deals. It brings insights forward without being asked. It monitors markets for shifts that affect value. It behaves like a digital team member, not just a tool.

This changes the skills deal teams need. Senior judgment becomes more valuable, not less. Teams that know how to direct, question, and govern AI gain a structural advantage.

Impact on Valuations and Timelines

With AI now at the center of execution, valuations shift. Companies with strong AI assets, including proprietary data, trained models, and proven use cases, see higher demand and faster processes. These companies earn premiums because buyers believe the value is durable.

Companies without these assets face tougher conversations. Their valuations rely more on traditional fundamentals. Their timelines expand as buyers investigate risk. Their deal probability shrinks if AI exposure creates uncertainty.

Regulation also affects timelines. Many dealmakers want clearer government oversight for AI. They want frameworks that set expectations and reduce uncertainty. Governance now carries weight in valuation discussions. Companies that follow emerging standards earn credibility with buyers and regulators.

The result is a market that rewards preparation and punishes opacity. Clean data, transparent models, strong controls, and documented performance are no longer ‘nice to have.’ They are prerequisites for a smooth, confident process.

What This Means for Founders and Investors

Founders heading into 2026 must adjust. The bar is higher. AI cannot be a late addition. It must be a core capability with clear evidence behind it. This means building proprietary data advantages early; retaining documentation for model training and performance; investing in governance and auditability; aligning product design to real use cases, and preparing for deeper technical diligence.

Investors must guide their portfolio companies with urgency. The market now assumes AI will shape valuation and risk. Investors must push for stronger data infrastructure; early alignment with governance standards; clear reporting on AI value creation; and talent that understands both AI and the business.

The Path Forward

Two scenarios could define 2026: rapid acceleration in deal volume or steadier growth shaped by regulatory complexity. Both scenarios rely on one constant, AI as core deal infrastructure.

The question is no longer whether AI will redefine M&A. The real question is how quickly teams adapt, and how well they manage the risks along the way. 2025 showed what was possible.
2026 makes it expected. Now is the time to act with purpose, build trust into the stack, and shape a smarter future for dealmaking.